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Effects of different irrigation methods on nitrous oxide emissions and ammonia oxidizers microorganisms in greenhouse tomato fields

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  • Ye, X.H.
  • Han, B.
  • Li, W.
  • Zhang, X.C.
  • Zhang, Y.L.
  • Lin, X.G.
  • Zou, H.T.

Abstract

Agricultural soils are strong sources of the potent greenhouse gas N2O but soil N2O emissions and its microbial mechanism in greenhouse field, especially ammonia-oxidizing microorganisms are unclear. We characterized a potential response in soil N2O production and its influencing factors, such as soil temperature, moisture, pH, and inorganic nitrogen to different irrigation methods named drip irrigation (DI), subsurface irrigation (SI) and furrow irrigation (FI) in a long-term irrigation field in greenhouse. The abundance and metabolic activity of ammonia oxidizing archaea (AOA) and bacteria (AOB) in greenhouse soils were also investigated using amoA gene as a molecular biomarker by quantitative PCR and 13CO2-DNA-stable isotope probing (SIP) methods. Results showed that N2O flux peaks would obviously occur within 1–8 days after each irrigation. The soil N2O flux in FI treatment was significantly higher than that in DI and SI treatments (P < 0.05). Correlation analysis between soil N2O flux and its influencing factors indicated that soil moisture and nitrate nitrogen were substantially affecting soil N2O emissions compared with soil temperature, pH and ammonium nitrogen. The copy numbers of AOA amoA gene in FI treatment were significantly higher than those in DI and SI treatments (P < 0.05), while there is no significant difference of AOB amoA gene among the three treatments. Also, the copy numbers of AOA amoA gene were significantly higher than those of AOB amoA gene. The 13CO2-DNA-SIP and phylogenetic tree results indicated only AOB dominantly involved in Nitrosospira genera was active during the nitrification process in the three irrigation methods. Our findings provided direct evidence that drip irrigation and subsurface irrigation could effectively reduce soil N2O emissions in greenhouse. AOA was dominant in abundance, while AOB played a key role in microbial community under the conditions of this experiment. Future characterization of the mechanisms for ammonia oxidation requires deeper studies in the greenhouse field.

Suggested Citation

  • Ye, X.H. & Han, B. & Li, W. & Zhang, X.C. & Zhang, Y.L. & Lin, X.G. & Zou, H.T., 2018. "Effects of different irrigation methods on nitrous oxide emissions and ammonia oxidizers microorganisms in greenhouse tomato fields," Agricultural Water Management, Elsevier, vol. 203(C), pages 115-123.
    • Handle: RePEc:eee:agiwat:v:203:y:2018:i:c:p:115-123
    DOI: 10.1016/j.agwat.2018.03.012
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    1. Amer, Kamal H., 2011. "Effect of irrigation method and quantity on squash yield and quality," Agricultural Water Management, Elsevier, vol. 98(8), pages 1197-1206, May.
    2. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6809), pages 184-187, November.
    3. Wang, Dan & Kang, Yaohu & Wan, Shuqin, 2007. "Effect of soil matric potential on tomato yield and water use under drip irrigation condition," Agricultural Water Management, Elsevier, vol. 87(2), pages 180-186, January.
    4. Zhang, Yajie & Niu, Haishan & Wang, Shiping & Xu, Kun & Wang, Rui, 2016. "Application of the DNDC model to estimate N2O emissions under different types of irrigation in vineyards in Ningxia, China," Agricultural Water Management, Elsevier, vol. 163(C), pages 295-304.
    5. Mark Trimmer & Panagiota-Myrsini Chronopoulou & Susanna T. Maanoja & Robert C. Upstill-Goddard & Vassilis Kitidis & Kevin J. Purdy, 2016. "Nitrous oxide as a function of oxygen and archaeal gene abundance in the North Pacific," Nature Communications, Nature, vol. 7(1), pages 1-10, December.
    6. Peter M. Cox & Richard A. Betts & Chris D. Jones & Steven A. Spall & Ian J. Totterdell, 2000. "Erratum: Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model," Nature, Nature, vol. 408(6813), pages 750-750, December.
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    1. Yin, Gaofei & Wang, Xiaofei & Du, Huiying & Shen, Shizhou & Liu, Canran & Zhang, Keqiang & Li, Wenchao, 2019. "N2O and CO2 emissions, nitrogen use efficiency under biogas slurry irrigation: A field study of two consecutive wheat-maize rotation cycles in the North China Plain," Agricultural Water Management, Elsevier, vol. 212(C), pages 232-240.
    2. Wenchao Cao & Su Liu & Zhi Qu & He Song & Wei Qin & Jingheng Guo & Qing Chen & Shan Lin & Jingguo Wang, 2019. "Contribution and Driving Mechanism of N 2 O Emission Bursts in a Chinese Vegetable Greenhouse after Manure Application and Irrigation," Sustainability, MDPI, vol. 11(6), pages 1-12, March.
    3. Mehmood, Faisal & Wang, Guangshuai & Abubakar, Sunusi Amin & Zain, Muhammad & Rahman, Shafeeq Ur & Gao, Yang & Duan, Aiwang, 2023. "Optimizing irrigation management sustained grain yield, crop water productivity, and mitigated greenhouse gas emissions from the winter wheat field in North China Plain," Agricultural Water Management, Elsevier, vol. 290(C).
    4. Wang, Jingwei & Li, Yuan & Niu, Wenquan, 2021. "Effect of alternating drip irrigation on soil gas emissions, microbial community composition, and root–soil interactions," Agricultural Water Management, Elsevier, vol. 256(C).
    5. Ding, Wuhan & Chang, Naijie & Zhang, Jing & Li, Guichun & Zhang, Jianfeng & Ju, Xuehai & Zhang, Guilong & Li, Hu, 2022. "Optimized fertigation mitigates N2O and NO emissions and enhances NH3 volatilizations in an intensified greenhouse vegetable system," Agricultural Water Management, Elsevier, vol. 272(C).
    6. Yasmen Heiba & Mahmoud Nasr & Manabu Fujii & Abdallah E. Mohamed & Mona G. Ibrahim, 2024. "Improving irrigation schemes using sustainable development goals (SDGs)-related indicators: a case study of tomato production in pot-scale experimentation," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(7), pages 17721-17747, July.
    7. Qi, Wei & Zhang, Zhanyu & Wang, Ce & Huang, Mingyi, 2021. "Prediction of infiltration behaviors and evaluation of irrigation efficiency in clay loam soil under Moistube® irrigation," Agricultural Water Management, Elsevier, vol. 248(C).

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    Keywords

    Soil N2O emissions; amoA gene; Greenhouse; qPCR; DNA-SIP;
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